GPT-5.4 Nano vs Qwen3.8 Flash
Qwen3.8 Flash costs 2.7x less per output token than GPT-5.4 Nano ($0.47 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 44.8
- Overall
- 45.7
- Output $/M
- $1.25
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.47
GPT-5.4 Nano or Qwen3.8 Flash: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3.8 Flash has none, so the two cannot be ranked on coding.
Pick Qwen3.8 Flash for output tokens 2.7x cheaper ($0.47 vs $1.25 per million) and a larger context window (1M against 400K tokens).
No benchmark has tested both yet. GPT-5.4 Nano has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GPT-5.4 Nano has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.4 Nano has a AA Intelligence Index result, 20.7.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Nano has a GPQA Diamond result, 77.5%.
Directional only
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Nano has a MMLU Pro result, 77.2%.
Directional only
Long documents
Listed context window
Qwen3.8 Flash
Qwen3.8 Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Flash
GPT-5.4 Nano $0.0008, Qwen3.8 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Nano has the number, $0.14.
Directional only
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, Qwen3.8 Flash not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5.4 Nano $1.25 against Qwen3.8 Flash $0.47 per million output tokens, 2.7x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, Qwen3.8 Flash 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only GPT-5.4 Nano measured |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.4 Nano measured |
| Vibe Code Bench (Vals AI) | 26.1% | Not measured | Only GPT-5.4 Nano measured |
| Code migration (Vals AI) | 14.5% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | Not measured | Only GPT-5.4 Nano measured |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only GPT-5.4 Nano measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: coding | 1404 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: software and IT | 1402 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | Not measured | Only GPT-5.4 Nano measured |
| Epoch Capabilities Index | 146.0 | Not measured | Only GPT-5.4 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | Not measured | Only GPT-5.4 Nano measured |
| LiveBench research | Not measured | 74.6% | Only Qwen3.8 Flash measured |
| LiveBench browser | Not measured | 48.0% | Only Qwen3.8 Flash measured |
| LiveBench long agentic | Not measured | 37.1% | Only Qwen3.8 Flash measured |
| Finance Agent (Vals AI) | 38.2% | Not measured | Only GPT-5.4 Nano measured |
| Tax Agent Bench (Vals AI) | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| Legal Research Bench (Vals AI) | 6.3% | Not measured | Only GPT-5.4 Nano measured |
| Excel Modeling Benchmark (Vals AI) | 44.8% | Not measured | Only GPT-5.4 Nano measured |
| τ²-Bench Telecom | 76.0% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | Not measured | Only GPT-5.4 Nano measured |
| LiveBench reasoning | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | Not measured | Only GPT-5.4 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Epoch AI run) | 78.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI | 51.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI-2 | 5.7% | Not measured | Only GPT-5.4 Nano measured |
| Chess puzzles | 45.0% | Not measured | Only GPT-5.4 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: expert | 1396 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts in English | 1387 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: diagrams | 1210 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | 1225 | Not measured | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | 39.7% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 87.8% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tiers 1 to 3 | 44.9% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5.4 Nano measured |
| ProofBench | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: math | 1405 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: mathematical work | 1409 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-5.4 Nano measured |
| LegalBench (Vals AI) | 77.9% | Not measured | Only GPT-5.4 Nano measured |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only GPT-5.4 Nano measured |
| TaxEval (Vals AI) | 67.4% | Not measured | Only GPT-5.4 Nano measured |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | Not measured | Only GPT-5.4 Nano measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: medicine and healthcare | 1369 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: legal and government | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: business and finance | 1366 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench design | Not measured | 72.8% | Only Qwen3.8 Flash measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index32 boards measured
| Benchmark | GPT-5.4 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 74.2% | Only Qwen3.8 Flash measured |
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | Not measured | Only GPT-5.4 Nano measured |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | Not measured | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 76.7% | Not measured | Only GPT-5.4 Nano measured |
| DTBench | 80.3% | Not measured | Only GPT-5.4 Nano measured |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: instruction following | 1362 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: creative writing | 1315 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: non-English | 1359 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Chinese | 1391 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: German | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | 1343 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | 1321 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: French | 1395 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Spanish | 1371 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | 1363 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Polish | 1366 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | 1382 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: longer queries | 1365 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: writing and language | 1338 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: entertainment and media | 1325 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: English | 1202 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | 1232 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | 1204 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | 1161 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | 1159 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 16 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.8 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.8 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.4 Nano | Qwen3.8 Flash |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | August 26, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $0.20 | $0.15 |
| Output $/Mtok | $1.25 | $0.47 |
| Coding index | 44.8 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.14 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than Qwen3.8 Flash for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3.8 Flash has none, so the two cannot be ranked on coding. Pick Qwen3.8 Flash for output tokens 2.7x cheaper ($0.47 vs $1.25 per million) and a larger context window (1M against 400K tokens).
Which is cheaper, GPT-5.4 Nano or Qwen3.8 Flash?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Qwen3.8 Flash costs $0.15 and $0.47. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Qwen3.8 Flash?
Qwen3.8 Flash, with 1M tokens against 400K.
Has any benchmark tested both GPT-5.4 Nano and Qwen3.8 Flash?
No benchmark has tested both yet. GPT-5.4 Nano has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead. Data as of October 22, 2026.